Associate Principal Engineer, AI Architect

Company Description

Requirements

• The role requires 9+ years of total experience and a software engineering background with strong Python depth.
• Candidates should have delivered production-grade Generative AI applications at scale.
• The role requires deep knowledge of LLM integration patterns, RAG systems, and AI-driven UX design.
• Strong system design skills are required across backend, frontend, and AI infrastructure layers.
• The candidate must have defined technical strategy and influenced architecture across teams or pods.
• Experience with microservices, APIs, scalable backend systems, and MLOps practices is required.
• MLOps experience should include CI/CD, model versioning, monitoring, and governance.
• Hands-on experience with MLflow, Vertex AI, Kubeflow, or similar tools is required.
• Deep cloud experience is required, especially with GCP, Vertex AI, BigQuery, and/or Databricks.
• The role requires understanding of enterprise AI security, privacy, governance, and responsible AI.
• The candidate must translate ambiguous business problems into durable technical architectures and influence senior stakeholders.

Responsibilities

• Convert client business use cases and technical requirements into elegant technical designs.
• Own architecture and technical vision for AI-powered applications using Python, React, and Generative AI.
• Design scalable, secure, and cost-efficient platforms for LLM inference, RAG pipelines, and agent orchestration.
• Define frontend architecture and UX patterns for AI-native applications.
• Lead GenAI workflows that combine LLMs, tools, APIs, structured data, and user context.
• Establish engineering standards for prompts, model integration, evaluation, and observability.
• Build reusable GenAI components, SDKs, and frameworks across teams or products.
• Partner with product, design, data, and business leaders on scalable solutions.
• Review designs and codebases, unblock teams, and raise engineering standards.
• Lead technical discovery, solutioning, and client or executive-facing workshops.
• Ensure enterprise readiness across security, privacy, compliance, governance, and responsible AI.
• Create design documentation, define technologies and patterns, conduct POCs, and resolve architecture or implementation issues.

Qualifications

• Bachelor’s or master’s degree in computer science, Information Technology, or a related field.